供应链绩效评价理论、方法及应用研究
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摘要
随着市场环境的变化,企业之间的竞争逐渐演变为供应链之间的竞争,供应链各参与主体如何整合资源,降低运作成本,提高运作水平,进一步培育和发展供应链竞争力,明晰供应链运作绩效也变得尤为重要。因此,关于供应链绩效评价的研究,也受到越来越多的科研工作者的广泛关注。供应链的绩效评价主要包括评价指标体系的构建和评价方法与方式的选择,但是直到目前为止,仍然没有被普遍接受的、具有较好系统性、科学性的供应链绩效评价指标体系,更多的只是对一些评价指标的简单罗列,忽视了指标的计量问题,忽视了供应链各个流程及各节点的绩效情况。供应链绩效方法主要是有AHP、DEA,以及平衡计分卡等方法,目前的方法大多属于普适性的一般评价方法,缺少针对具体供应链绩效的求解方法,指标与方法之间结合度不够,这些都是供应链绩效评价过程中亟需解决的问题。因此,深入系统的开展供应链绩效评价模型研究有着重要的理论和现实意义。本文将针对以上问题从三个方面解决供应链绩效评价的问题。
     首先,建立了基于五维平衡积分卡和LMBP算法的供应链绩效评价模型。针对供应链绩效评价指标权重处理存在的诸多问题以及绩效结果的处理速度问题,本文首先在综合比较分析和评价各种典型仿生算法的基础上,结合五维平衡积分卡建立供应链绩效评价指标体系,利用仿生神经网络方法中的LMBP(Levenberg-MarquardtBackpropagation)算法快速计算网络权值、单隐含层BP网络整体训练速度快等特点,提出了基于LMBP算法的供应链绩效评价模型与方法。通过对供应链绩效评价指标的各类数据归一化处理,建立LMBP神经网络模型,通过迭代训练,确定权值及绩效评价状态,从而进一步分析、评价供应链运作绩效。在案例分析中,用Matlab设置了训练参数,训练结果证明了该模型准确高效,并分析供应链绩效不佳的主要原因,提出改进优化方案,为后续供应链绩效改进提供理论支持。
     其次,结合业务流程建模理论,提出了基于业务流程建模的供应链绩效评价模型(Business Process Modeling for Supply Chain Performance Evaluation,BPM-SCPE)的理论架构。为了进一步识别供应链子系统的绩效,以及更为重要的供应链效率的考核等问题,本文通过业务流程建模,运用流程图直观形象地将各层级各环节的供应链运作状态表示出来,首次将业务流程建模的理论方法和技术应用于供应链绩效评价中,利用业务流程建模IDEF技术,针对以降低成本、提高顾客满意度为目标的供应链绩效评价,剖析了供应链顶层及分阶段业务流程建模的输入、输出、控制和机制四个要素,构建供应链业务流程顶层及分层功能模型,展示了供应链业务流程全过程及各子供应链相互关系,并在此基础上,建立了基于业务流程建模的供应链绩效评价方法,构建了以供应链业务流程投入主要成本要素为考量重点的有形绩效评价指标体系和以顾客满意度为主的无形绩效评价指标体系,以全新视角构架了供应链绩效全面评价模型。
     再次,构建BPM-SCPE综合模型的各类指标计算方法。基于BPM-SCPE评价模型,在供应链顶层业务流程设计过程中,构建了劳动力成本模型、设施设备应用成本模型、原材料成本模型、固定资产成本模型、信息系统管理成本模型、技术创新成本模型。首次提出了以时间维度为考量重点的建模思想,利用回归分析等方法使供应链业务流程运行成本核算更客观、准确。此外,结合时间、质量、可靠性、柔性、安全性等传统的供应链绩效评价指标特点,构建各指标计算方法,利用BPM-SCPE评价方法的指导思想,对整条供应链进行分阶段绩效评价,最终得出整体供应链绩效评价结果。通过以皓月集团为核心企业的生鲜牛肉供应链绩效评价的实证分析,进一步验证了该绩效评价方法理论上的先进性与可行性。该方法从理论上能够较好地监控供应链业务流程各阶段的绩效状况,实现供应链绩效全面评价与分段评价的统一。同时追溯绩效不佳的根源,提出改进优化方案,对于供应链整体竞争和供应链各成员企业的业务操作具有指导意义。
     因此,全文在剖析传统供应链绩效评价过程存在问题的基础上,最终得出两种解决供应链绩效评价问题的方法。一是在改进的五维平衡计分卡的供应链绩效评价方法基础上,使用新的算法――LMBP仿生算法,能够更准确更快捷合理地评价供应链整体绩效水平,并利用案例研究,展示了利用该评价方法对预测供应链绩效水平和改进供应链绩效的优势;二是利用业务流程建模技术,结合供应链模型的各节点各层级实际运作产生的成本要素,构建全新的供应链绩效评价模型,突出供应链效率的测定,使供应链整体绩效评价更直观可视,并兼顾了整体和局部供应链绩效的全面评价。通过实证研究,验证了新绩效评价模型的高效性,同时对供应链绩效低的原因及改良方案进行了初步探讨。本文对于供应链绩效评价新方法的探索性研究,对于供应链绩效评价体系的理论完善与实际业务运行具有一定的创新性和指导性。
With the change of market environment, the competition between enterprises hasevolved into the competition between supply chains. How to integrate resources, reduceoperating costs, improve operational level, further cultivate and develop competitivenessand make clear the operation performance of supply chain have become particularlyimportant to supply chain participants. So the study on supply chain performanceevaluation has been paid close attention by more and more researchers. The supply chainperformance evaluation mainly includes the construction of the evaluation index systemand the choice of evaluation methods and ways. Supply chain performance index systemsnow constructed are various and give the reference system from different perspectives.However, there is still no such a systemic and scientific supply chain performanceevaluation index system that could be widely accepted till now. More of them are just asimple list of some evaluation index, which ignore the measurement problems ofindicators and the performance situation of each node of the supply chain. The mainmethods to measure the supply chain performance evaluation include AHP, DEA, andbalanced score card, etc. they mostly belong to the general and universal evaluationmethods, lack of concrete solution method of supply chain performance, the combineddegree between indexes and methods are insufficient, these problems need to be solvedurgently during the process of supply chain performance evaluation. Therefore, the studyon the supply chain performance evaluation model deeply and systematically hasimportant theoretical and realistic significance. This paper intends to solve the problems ofsupply chain performance evaluation in the view of above three questions.
     First, this paper established the model of supply chain performance evaluation based onfive dimension balanced score card and LMBP algorithm. Aimed at the problems of indexweight process of supply chain performance evaluation and process speed of performanceresults, this paper first constructed the supply chain performance evaluation index systemcombined with five dimension balanced score card from bionics view, and established themodel and method of supply chain performance evaluation based on LMBP algorithm.Through normalization process to various kinds of data of supply chain performanceevaluation index to establish LMBP neural network model, through iterative training toidentify the weights and performance evaluation status, then further analyzed and evaluated the supply chain performance. Through repeated experiments of LMBPalgorithm to get the minimum error of entire network using Purelin function from inputlayer to hidden layer and from hidden layer to output layer. In the case study, the trainingparameters were set up through the Matlab, the training results proved that the model wasaccurate and efficient, then analyzed the main reasons of poor performance of supplychain, and put forward the improvement scheme, which could provide theoretical supportfor the subsequent improvement of supply chain performance.
     Second, combining with business process modeling theory, this paper put forward thetheoretical framework of Business Process Modeling for Supply Chain PerformanceEvaluation (BPM-SCPE). In order to further identify the supply chain performance ofsub-system, as well as assess the efficiency of supply chain, this paper presented thesupply chain operation status of all levels and links by flow chart through business processmodeling, first applied the theory and technology of business process modeling to thesupply chain performance evaluation, used IDEF0technique of business process modeling,aimed at cost reduce and customer satisfaction improvement of supply chain performanceevaluation, analyzed the four elements of top layer of supply chain and stages of businessprocess modeling, which were input, output, control and mechanism, constructed the toplayer and layered function model of supply chain business process, showed the wholeprocess of supply chain business process and the interrelationship between sub supplychains. On this basis, established the supply chain performance evaluation based onbusiness process modeling method, constructed the physical performance evaluation indexsystem focused on invested cost and intangible performance evaluation index systemfocused on customer satisfaction, established a comprehensive supply chain performanceevaluation model from a brand-new perspective.
     Last, this paper constructed the calculation method of all kinds of index ofBPM-SCPE evaluation method. Based on BPM-SCPE evaluation model, during theprocess of top layer business process design of supply chain, constructed the labor costmodel, facilities and equipment application cost model, raw materials cost model, fixedassets cost model, information system management cost model, technologicalinnovation cost model. First proposed the modeling idea focused on timedimension, made the business process operation cost of supply chain more objectiveand more accurate using the regression analysis methods. In addition, combined withthe characteristics of traditional supply chain performance evaluation indexof time, quality, reliability, flexibility, safety, constructed the calculation methods of each index, used the guiding ideology of BPM-SCPE evaluation method, evaluatedeach stage performance of entire supply chain, finally obtained the overall supplychain performance evaluation results. Through the empirical analysis of fresh beef supplychain performance evaluation by Haoyue group, further verified the advancementand feasibility in theory of this performance evaluation method. This method couldbetter monitor each stage performance situation of supply chain business process intheory, and realize the unity of comprehensive evaluation and staged evaluation of supplychain performance. At the same time, traced the roots of poor performance, and putforward the improvement scheme, which had great guiding significance for the wholesupply chain competition and the business operation of member enterprises of supplychain.
     Therefore, this paper finally obtained two kinds of methods to solve the problems ofsupply chain performance evaluation after analyzed the existing problems of traditionalsupply chain performance evaluation process. One was based on the improved fivedimension balanced score card of supply chain performance evaluation method, using thenew LMBP bionic algorithm, could evaluate the whole supply chain performance levelmore accurately, more quickly and more rationally, and demonstrated the advantage offorecasting supply chain performance level and improving poor supply chain performancethrough this evaluation method by case study; The other one was combined with theactual operation cost of each level and each node of supply chain model, constructed abrand-new supply chain performance evaluation model by business process modelingtechnology, focused on supply chain efficiency measurement, made the overall supplychain performance evaluation more intuitive and more visual, covered both overall andpartial supply chain performance evaluation. Through empirical research, verified the highefficiency of new performance evaluation model, discussed the causes of poor supplychain performance and improvement scheme. The exploratory research of new supplychain performance evaluation method in this paper has innovativeness and instructivefor theory improvement and practical business operation of supply chain performanceevaluation system.
引文
[1]马士华,林勇.供应链管理[M].北京:机械工业出版社,2005.
    [2]唐纳德J.鲍尔索克斯,戴维J.克劳斯,M.比克斯比.库珀.供应链物流管理[M].北京:机械工业出版社,2011.
    [3] Christopher M. Logistics and supply chain management: strategies for reducing costand improving service. London[J]. Financial times,1998.
    [4]刘晋.供应链管理:企业提高竞争力的有效途径[J].经济管理文摘,1996,6:22-24.
    [5] Pittiglio Rabin Todd&Mcgrath (PRTM).Strategic Supply Chain [EB/OL].(2002-12-01)
    [2012-10] http://www.pwc.com/gx/en/operations-consulting-services/publications/supply-chain-anagement.
    [6]王龙昭.基于仿生理论的供应链绩效评价研究[D].长春:吉林大学硕士学位论文,2012.
    [7] Hendricks K B, Singhal V R. The effect of supply chain glitches on shareholderwealth[J]. Journal of Operations Management,2003,21(5):501-522.
    [8]中国物流与采购联合会.中国制造业供应链报告[R].北京:[出版者不详],2004.
    [9]查敦林.供应链绩效系统研究[D].南京:南京航空航天大学博士学位论文,2003.
    [10]曲盛恩.供应链绩效评价的系统研究[D].哈尔滨:哈尔滨工程大学,2006.
    [11] Xuemei Fan, Shujun Zhang, Longzhao Wang, Yinsheng Yang, Kevin Hapeshi. AnEvaluation Model of Supply Chain Performances Using5DBSC and LMBP NeuralNetwork Algorithm [J]. Journal of Bionic Engineering,2013,10(3):383-395.
    [12]肖振伟.供应链效率问题研究[G].西安:西安电子科技大学硕士学位论文,2005.
    [13]孙桂林.供应链效率优化问题研究[G].西安:西安交通大学硕士学位论文,2008.
    [14] Tan K C. A framework of supply chain management literature[J]. European Journal ofPurchasing&Supply Management,2001,7(1):39-48.
    [15]陈畴墉,于俭,曹为国,王晓耘.电子商务供应链管理[M].大连:东北财经大学出版社,2002.
    [16] Weerasinghe, Shivanthi. Revolution within the revolution: the Sri Lankan attempt tobridge the digital divide through e-governance [J]. International Information&Library Review.2004,36(4):319-327.
    [17]马士华,李华焰,林勇.平衡计分卡在供应链绩效评价中的应用研究[J].工业工程与管理,2002,4:5-9.
    [18]蹇崇军.供应链管理系统集成建模方法研究及系统实现[D].西安:西北工业大学博士学位论文,2006.
    [19]姜辉.大型煤炭企业内部供应链的构建与优化研究[D].徐州:中国矿业大学博士学位论文,2009.
    [20] Friedman T L. The world is flat3.0: A brief history of the twenty-first century[M].Macmillan,2007.
    [21]中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会. GB/T18354-2006中华人民共和国国家标准[S].北京:中国标准出版社,2007.
    [22]李书芳.智慧城市建设与频谱资源管理[Z].2012两岸物联网合作交流论坛,2012
    [23]钮钢.物联网及智慧城市发展趋势和产业机会[Z].2012两岸物联网合作交流论坛,2012
    [24]佟金,王亚辉,樊雪梅,张书军,陈东辉.农产品冷链物流状态监控信息系统[J].吉林大学学报(工学版).2013,43(06):1707-1711.
    [25] Grover V, Teng J T C, Fiedler K D. Investigating the role of information technologyin building buyer-supplier relationships[J]. Journal of the Association for InformationSystems (Volume3,2002),2003,217(245):245.
    [26] Wiley, Amazon, Barnes&Noble. Performance Analysis [EB/OL].(2002-12-01)
    [2012-10]http://planningdrupalsites.com/guide/collect-requirements/performance-analysis.
    [27] Bititci U S, Carrie A S, McDevitt L. Integrated performance measurement systems: adevelopment guide[J]. International Journal of Operations&Production Management,1997,17(5):522-534.
    [28] Neely, A.D., Mike Gregory, Ken Platts. Performance measurement system design: Aliterature review and research agenda[J]. International Journal of Operations&Production Management,1995,15(4):80–116.
    [29]贾燕.供需链设计优化模型及其复杂性问题研究[D].西安:西北工业大学博士学位论文,2002.
    [30] Chan F T S, Qi H J. An innovative performance measurement method for supplychain management[J]. Supply Chain Management: An International Journal,2003,8(3):209-223.
    [31] Supply-Chain Council (SCC).Supply chain operations reference model[M]. SupplyChain Council,2008.
    [32] Lummus R R, Vokurka R J, Alber K L. Strategic supply chain planning[J].Production and Inventory Management Journal,1998,39:49-58.
    [33] Beamon B.M. Measuring supply chain performance[J]. International Journal ofoperations and Production Management.1999,19(3):275-292.
    [34] Gunasekaran A, Patel C, Tirtiroglu E. Performance measures and metrics in a supplychain environment[J]. International journal of operations&production Management,2001,21(1/2):71-87.
    [35] Conet Consulting AG. Supply Chain[EB/OL].(2002-9-25)[2012-10] www.conet.de.
    [36]徐贤浩,马士华,陈荣秋.供应链绩效评价特点及其指标体系研究[J].华中理工大学学报(社会科学版),2000,2(14):69-72.
    [37]中国电子商务协会供应链管理委员会.中国企业供应链管理绩效水平评价参考模型(SCPR1.0)[M].北京:[出版社不详],2003.
    [38]席一凡,姚树俊,李继军,何萱.模糊优选法在绿色供应链合作关系评价中的应用[J].价值工程.2007,4:69-71.
    [39]郑培.动态供应链绩效评价方法研究[D].长沙:湖南大学博士学位论文,2008.
    [40] Bolch, G., Greiner, S., de Meer, H., Trivedi, K. S. Queuing Networks and MarkovChains Modeling and Performance Evaluation with Computer Science Applications(2nd Edition)[M]. A John Wiley&Sons, Inc., publication,2006.
    [41] Beamon B M. Measuring supply chain performance[J]. International Journal ofOperations&Production Management,1999,19(3):275-292.
    [42]王龙昭.基于仿生理论的供应链绩效评价研究[D].长春:吉林大学硕士学位论文,2012.
    [43] Gunasekaran A, Patel C, McGaughey R E. A framework for supply chainperformance measurement[J]. International journal of production economics,2004,87(3):333-347.
    [44]赵林度.供应链与物流管理[M].北京:机械工业出版社,2007.
    [45]百度百科.PMS [EB/OL].(2012-7-29)[2012-10] http://baike.baidu.com/view/699333.htm.
    [46] Kaplan R S, Norton D P. The strategy focused organization: How balanced scorecardcompanies thrive in the new business environment[M]. Boston: Harvard BusinessPress,2001.
    [47] Kaplan R., Norton D. The Strategy Focused Organization [M]. Boston: HarvardBusiness School Press, USA,2000.
    [48]郑培.动态供应链绩效评价方法研究[D].长沙:湖南大学博士学位学位论文,2008.
    [49]陈科.制造型供应链绩效建模分析研究与实践[D].天津:天津大学博士学位论文,2009.
    [50]中国物流学会.第三届中国物流学术年会论文集[R].北京:[出版者不详],2004.
    [51]徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法[M].北京:科学出版社,2003.
    [52] Pawlak Z. Rough sets, decision algorithms and Bays' theory[J].European Journal ofOperational Research,2002,136(1):181-189.
    [53]史成东,陈菊红,胡健.基于粗糙集和神经网络的供应链绩效预测研究[J].计算机工程与应用,2007,43(33):203-245.
    [54]姜波.供应链绩效评价体系研究[D].北京:中国石油大学硕士学位论文,2007.
    [55]席一凡,王超,聂兴信.基于模糊神经网络的供应链绩效评价方法研究[J].情报杂志,2007,9:77-79.
    [56]文培娜,张志勇,罗斌.基于BP神经网络的北京物流需求预测及分析[J].技术与方法,2009,6:91-93.
    [57] Fang-ming Z, Qing-kui C, Qiao-yun W. A comparative inquiry into supply chainperformance appraisal based on Support Vector Machine and neuralnetwork[C]//Management Science and Engineering,2008. ICMSE2008.15th AnnualConference Proceedings., International Conference on. IEEE,2008:370-377.
    [58]李艳.GA和SVM在供应链绩效评价中的应用[J].计算机工程与应用,2010,46(1):246-248.
    [59]于金梅.遗传算法在供应链网络设计中的应用[D].广州:华南理工大学硕士学位论文,2011.
    [60] Gabbert, P., Brown, D. E., Huntley, C. L., Markowicz, B. P., Sappington, D. E. ASystem for Learning Routes and Schedules with Genetic Algorithms[C]//ICGA.1991:430-436.
    [61]刘诚.供应链网络优化—建模与理论设计[D].长沙:中南大学博士学位论文,2006.
    [62]吴学静,周泓,梁春华.基于协同进化粒子群的多层供应链协同优化[J].计算机集成制造系统,2010,16(1):127-132.
    [63]何佳.粒子群神经网络在供应链库存管理中的应用[D].贵州:贵州大学硕士学位论文,2007.
    [64]王辉.供应链集成化模型与优化[D].北京:北京交通大学硕士学位论文,2007.
    [65]丁秀明.基于蚁群优化的供应链调度算法研究一一物流调度算法研究[D].无锡:江南大学硕士学位论文,2008.
    [66]李金津.企业生态链理论研究[D].长春:吉林大学博士学位论文,2011.
    [67] Bell J E, McMullen P R. Ant colony optimization techniques for the vehicle routingproblem[J]. Advanced Engineering Informatics,2004,18(1):41-48.
    [68] Montemanni R, Gambardella L M, Rizzoli A E, et al. Ant colony system for adynamic vehicle routing problem[J]. Journal of Combinatorial Optimization,2005,10(4):327-343.
    [69]刘云忠,宣慧玉.蚂蚁算法在车辆路径问题中的应用研究[J].信息与控制,2004,33(2):249-252.
    [70]万旭,林健良,杨晓伟.改进的最大——最小蚂蚁算法在有时间窗车辆路径问题中的应用[J],计算机集成制造系统,2005,11(4):572-576.
    [71]戴树贵.物流系统模型和算法研究[D].上海:华东师范大学博士学位论文,2007.
    [72] Paul R J, Macredie R D. Guest editorial: Managing dynamic requirements[J].Requirements Engineering,1999,4(2):63-64.
    [73] Warren P H. Dispersal and destruction in a multiple habitat system: an experimentalapproach using protist communities[J]. Oikos,1996:317-325.
    [74] William J. Kettinger, James T. C., Guha S. Business Process Change: A Study ofMethodologies, Techniques, and Tools [J]. MIS Quarterly,1997,1(21):55-80.
    [75] Hommes B J, Van Reijswoud V. Assessing the quality of business process modellingtechniques[C]//System Sciences,2000. Proceedings of the33rd Annual HawaiiInternational Conference on. IEEE,2000.
    [76] Luo W, Tung Y A. A framework for selecting business process modeling methods[J].Industrial Management&Data Systems,1999,99(7):312-319.
    [77] Curtis P. Mudding: Social phenomena in text-based virtual realities[J]. High noon onthe electronic frontier: Conceptual issues in cyberspace,1992:347-374.
    [78] Kendall W L, Pollock K H, Brownie C. A likelihood-based approach tocapture-recapture estimation of demographic parameters under the robust design[J].Biometrics,1995:293-308.
    [79]陈禹六. IDEF建模分析和设计方法[M].北京:清华大学出版社,1999.
    [80]贺清碧. BP神经网络及应用研究[D].重庆:重庆交通学院硕士学位论文,2004.
    [81]李晓峰,刘光中.人工神经网络BP算法的改进及其应用[J].四川大学学报(工程科学版),2000,32(2):105-109.
    [82]张利,吴华玉,卢秀颖.基于粗糙集的改进BP神经网络算法研究[J].大连理工大学学报,2009,49(6):972-976.
    [83] Rumelhart D E, Hintont G E, Williams R J. Learning representations byback-propagating errors[J]. Nature,1986,323(6088):533-536.
    [84] Masters T. Advanced Algorithms for Neural Networks: a C11Sourcebook [M]. Wiley,New York, USA,1995.
    [85] Turkle S. Constructions and reconstructions of self in virtual reality: Playing in theMUDs[J]. Mind, Culture, and Activity,1994,1(3):158-167.
    [86] Hornik K, Stinchcombe M, White H. Multilayer feedforward networks are universalapproximators[J]. Neural networks,1989,2(5):359-366.
    [87] Curtis B, Kellner M I, Over J. Process modeling[J]. Communications of the ACM,1992,35(9):75-90.
    [88] Lin F R, Yang M C, Pai Y H. A generic structure for business process modeling[J].Business Process Management Journal,2002,8(1):19-41.
    [89] Fynes B, De Búrca S, Marshall D. Environmental uncertainty, supply chainrelationship quality and performance[J]. Journal of Purchasing and SupplyManagement,2004,10(4):179-190.
    [90] Swafford P M, Ghosh S, Murthy N. The antecedents of supply chain agility of a firm:scale development and model testing[J]. Journal of Operations Management,2006,24(2):170-188.
    [91] Chang, S. C., Yang, C. L., Cheng, H. C.,&Sheu, C. Manufacturing flexibility andbusiness strategy: an empirical study of small and medium sized firms[J].International Journal of Production Economics,2003,83(1):13-26.
    [92] Kuglin F A. Customer-centered supply chain management: a link-by-link guide[M].Amacom,1998.
    [93] Beamon B M. Measuring supply chain performance[J]. International Journal ofOperations&Production Management,1999,19(3):275-292.
    [94] Chan F T S, Qi H J. Feasibility of performance measurement system for supply chain:a process-based approach and measures[J]. Integrated Manufacturing Systems,2003,14(3):179-190.
    [95] Paul Sch nsleben. Integrales Logistik Management[M]. Springer DE,2004.
    [96] Stewart, G. Supply chain performance benchmarking study reveals keys to supplychain excellence[J]. Logistics Information Management,1995,8(2):38-44.
    [97] Craig Shepherd, Hannes Günter. Measuring supply chain performance: currentresearch and future directions[J]. International Journal of Productivity andPerformance Management,2006,55(3/4):242–258.
    [98] Gunasekaran A., Patel C., Tirtiroglu E. Performance measures and metrics in a supplychain environment [J]. International Journal of Operations&Production Management,2001,21(1/2):71–87.
    [99] Gunasekaran, A., Patel, C., Ronald, McGaughey E. A framework for supply chainperformance measurement[J]. International Journal of Production Economics,2004,87(3):333-347.
    [100]陈国华.汽车供应链可靠性若干关键技术研究[D].重庆:重庆大学博士学位论文,2011.
    [101]张艳东.供应链可靠性度量与优化[D].秦皇岛:燕山大学硕士学位论文,2010.
    [102] Gupta Y P, Goyal S. Flexibility of manufacturing systems: concepts andmeasurements[J]. European journal of operational research,1989,43(2):119-135.
    [103] Chen I J, Calantone R J, Chung C H. The marketing-manufacturing interface andmanufacturing flexibility[J]. Omega,1992,20(4):431-443.
    [104] Jordan W C, Graves S C. Principles on the benefits of manufacturing processflexibility[J]. Management Science,1995,41(4):577-594.
    [105] Lyons A C. Evaluating operations flexibility in industrial supply chains to supportbuild-to-order initiatives[J]. Business Process Management Journal,2007,13(4):572-587.
    [106]齐懿冰.供应链柔性演化及与绩效关系研究[D].长春:吉林大学博士学位论文,2010.
    [107]雷征.供应链安全及其成本关系研究[D].武汉:华中科技大学硕士学位论文,2008.
    [108]刘刚.供应链管理[M].北京:化学工业出版社,2005.
    [109]张伯生.确定权重的一种综合方法[J].上海:上海工程技术大学学报,1999,1(13),27-32.
    [110]王雪冬,李广杰,孟凡奇,黄勇,彭帅英.基于改进型拉开档次法的泥石流危险度评价实例[J].吉林大学学报(地球科学版),2012,6(42):1853-1858.
    [111]王斯锋,孙超,屈彪.基于三角函数的OWA算子赋权方法[J].曲阜师范大学学报,2012,1(38):25-29.

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